The ability to perform instrumental activities of daily living (IADL) allows individuals to live independently. Several evaluation tools can be used to evaluate IADL. Although questionnaire-based evaluation tools are widely used, they have the issue of potentially being reported differently than the participants' actual abilities. Virtual reality-based IADL (VR-IADL) programs have been proposed for improved assistance and evaluation. However, previous VR-IADL programs had limited scenarios and were difficult to use. To overcome this, we developed a ten-scenario version of a tablet-based VR-IADL program. To test the performance of the tablet-based VR-IADL program, two studies were performed. In Study 1, we recruited 20 healthy adults to develop the VR-IADL scoring system, and in Study 2, 31 patients with idiopathic rapid eye movement sleep behavior disorder were recruited to test its validity. Participants in Study 2 were considered to be at high risk of mild cognitive impairment, dementia, and Parkinson's disease. The results suggest that the VR-IADL score was positively correlated with cognitive tests and these correlations were better than those determined using existing tools. We believe that our tablet-based VR-IADL program is beneficial for older adults at high risk for neurodegenerative diseases.

As one of autonomous vehicles, conditional autonomous vehicles is expected to become popular in the near future. Conditional autonomous vehicles can send a take-over request (TOR) to a driver, and if they are immersed in non-driving-related tasks (NDRT), they will struggle to accommodate this request. Previous studies have shown that providing augmented reality (AR) information on traffic situations (status cues) or driver actions (command cues) can improve TOR performance. However, we are not aware of any studies comparing the types of AR cues (state versus command cues) and their interactions with environmental factors. Therefore, the current study investigated this and evaluated the TOR performance of 42 drivers. We used a 2 (environments: day and night) $\times$ 4 (AR cue types: without, status, command, and combined cues) mixed-subject experimental design, and dependent measures included driving, cognitive, and NDRT performances. The results suggest that overall driving and cognitive performance were significantly improved by the command AR cue. In contrast, the status AR cue improved the TOR performance in nighttime environments. The performance of AR cues can vary depending on environmental factors, and AR cue designs for autonomous vehicles should consider this interaction for successful collaboration between drivers and vehicles.

Conditional autonomous vehicles have attracted significant attention, and their wide-spread use is expected to further increase in the near future. However, such vehicles can send take-over requests (TORs) to a driver who may struggle to accommodate the request while immersed in non-driving-related tasks. Previous studies have focused on TOR times and cues; however, the effects of environmental conditions have not been examined rigorously. This study, with the aim of addressing the aforementioned issue, is divided into two parts: in Study 1, we examine driver responses to TORs under different environmental conditions (i.e., sunny, rainy, snowy, foggy, and night-time), and in Study 2, we examine the effects of the proposed TOR cues (augmented reality + smartphone alert) under different environmental conditions. For this investigation, a driving simulator was used for the participants’ safety. Each study involves 33 participants. The results of Study 1 indicate significant differences in the take-over time, lane-change time, time-to-collision, maximum acceleration, and subjective mental workload corresponding to different environmental conditions. Furthermore, the results of Study 2 suggest that the proposed TOR cues significantly reduce the effects of environmental conditions on various take-over performances. We discuss the implication of these results in terms of the improvements in responses to TORs and investigation of the effects of environmental conditions on the responses to TORs.